ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Filtering by
- All Subjects: Sustainability
- All Subjects: microstructure quantification
- Creators: Chawla, Nikhilesh
The current study focuses on the fundamental understanding of such functional composites, from their microstructural design to macro-scale application. More specifically, this study investigates three different categories of functional cementitious composites. First, it discusses the differences between cementitious systems containing interground and blended limestone with and without alumina. The interground systems are found to outperform the blended systems due to differential grinding of limestone. A novel approach to deduce the particle size distribution of limestone and cement in the interground systems is proposed. Secondly, the study delves into the realm of ultra-high performance concrete, a novel material which possesses extremely high compressive-, tensile- and flexural-strength and service life as compared to regular concrete. The study presents a novel first principles-based paradigm to design economical ultra-high performance concretes using locally available materials. In the final part, the study addresses the thermal benefits of a novel type of concrete containing phase change materials. A software package was designed to perform numerical simulations to analyze temperature profiles and thermal stresses in concrete structures containing PCMs.
The design of these materials is accompanied by material characterization of cementitious binders. This has been accomplished using techniques that involve measurement of heat evolution (isothermal calorimetry), determination and quantification of reaction products (thermo-gravimetric analysis, x-ray diffraction, micro-indentation, scanning electron microscopy, energy-dispersive x-ray spectroscopy) and evaluation of pore-size distribution (mercury intrusion porosimetry). In addition, macro-scale testing has been carried out to determine compression, flexure and durability response. Numerical simulations have been carried out to understand hydration of cementitious composites, determine optimum particle packing and determine the thermal performance of these composites.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.